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系統識別號 U0026-0209202016221800
論文名稱(中文) 訓練衝量指標與急性疲勞之相關研究
論文名稱(英文) Research on Training Impulse Index and Acute Fatigue
校院名稱 成功大學
系所名稱(中) 體育健康與休閒研究所
系所名稱(英) Institute of Physical Education, Health & Leisure Studies
學年度 108
學期 2
出版年 109
研究生(中文) 何蔡萱
研究生(英文) Tsai-Hsuan Ho
學號 RB6074014
學位類別 碩士
語文別 中文
論文頁數 64頁
口試委員 指導教授-林麗娟
口試委員-張乃仁
口試委員-張升懋
口試委員-林泰祐
口試委員-鐘孟良
中文關鍵字 RPE訓練衝量法  心率變異性  HRV  垂直跳  血乳酸  人臉辨識 
英文關鍵字 session RPE  heart rate variability  HRV  vertical jump  blood lactate  remote photoplethysmography 
學科別分類
中文摘要 訓練的最終目的都是希望能增進運動員的表現,避免疲勞的累積使表現下降或提高受傷發生率,因此訓練負荷的監控是日顯重要。近年來國外的研究多以運動強度自覺量表(Rating of perceived exertion, RPE)所衍伸的RPE訓練衝量法(session RPE, sRPE)來監控訓練負荷,在國內卻少有實際應用sRPE的研究。安靜狀態下之心率變異性(Heart rate variability, HRV)是目前監控運動員是否為慢性疲勞狀態的有效方法之一,但在運動時HRV的評估是否能反應立即性的耗竭或疲勞可進一步評估。且近年來在科技與演算法的進步下發展出以人臉影像偵測心率與心率變異性的技術(rPPG),若能以RPE搭配HR、HRV以及垂直跳、血乳酸等已被陸續提出的監控策略,可找出訓練衝量指標與急性疲勞之間的關聯性,同時驗證rPPG的方式應用於運動訓練的可行性,期望能在未來提供教練在實際場域更簡單有效的監控指標與方法。
目的:探討在最大努力運動測試中,rPPG測得之心率與Polar H10測得之心率的趨勢相關性,並藉由監控內在訓練負荷的指標,而提早發現力竭的預警點,提供教練調整訓練負荷之參考。
方法:22位規律運動的男大專生(age:23.15±1.67yrs)為受試者,每位受試者進行一至三次的跑步機最大努力運動測試。測試前後會分別進行神經肌肉測試(垂直跳)、血乳酸、安靜心跳率和HRV之RR intervals的量測,於跑步測試期間每分鐘以Foster10分量表的運動強度自覺量表(RPE scale)紀錄受試者自覺努力的分數,同步收錄受試者之運動心跳率、RR intervals以及能量代謝指標(包含攝氧量、呼吸交換率),測驗結束後立即以人臉影像記錄5分鐘。以R語言以及SPSS20.0統計軟體進行資料轉換與統計分析。以皮爾森積差相關 (Pearson correlation)比較RPE訓練衝量與能量代謝系統(%VO2peak)的相關性;單因子變異數分析(one-way ANOVA)比較跑步測驗中RPE的分數與相對應的疲勞指標,以及心率、垂直跳高度和血乳酸濃度在跑步測驗前後的差異,用以判斷RPE在耗竭運動的預警分數;以逐步迴歸分析探討反應血乳酸的因子。
結果:經排除VO2peak小於50mL/min/kg之受試者共收錄30人次的實驗,獲得590397筆的測驗數據驗證得出,在%HRmax、%VO2peak、呼吸交換率(R)以及HRV之相關指標的變化趨勢中,RPE為8分時,各項生理指標均較RPE為6分時有顯著的變化(p < .05),但在RPE為8分及9分之間多無顯著差異,表示RPE為8分時可為耗竭前的預警分數;以RPE為7分和8分時的訓練衝量與%VO2peak呈顯著相關(p < .01)。心率、血乳酸濃度以及垂直跳高度三項指標在各測量時間點之間均有顯著差異,表示此最大努力運動測試能有效使受試者處於急性疲勞狀態;其中,心率可作為有效預測血乳酸的方法,而血乳酸之變化量則以垂直跳的變化量作為預測方法。以429603筆Polar H10和rPPG的數據驗證得出,雖rPPG以及Polar H10兩者測得的心率數值成低強度的顯著相關( r= 0.147, p <.001),但二者也有顯著差異(p <.001),表示rPPG之技術需做進一步的調整方能與Polar H10有較明顯之相同趨勢。
結論:在運動狀態下的心率變異性相關指標中,以時域分析法所得的SDNN搭配RPE的使用就能預測耗竭的發生,而RPE為8分時似乎能作為耗竭發生前的預警並且以垂直跳的量測能有效在實際場域看出即時疲勞的狀態。心率可作為有效預測血乳酸的方法。在運動情境下以rPPG測得之心率需克服更多外在因素的影響,並需在演算法上做進一步的修正,期望未來能將此技術應用於運動疲勞偵測上。
英文摘要 Introduction: For athletes, the final goal of training is to improve their performance and to avoid fatigue, which may lower performance or increase the risk of injuries. Therefore, it is necessary to monitor training load. In recent years, many studies abroad have used the session RPE (sRPE) derived from the rating of perceived exertion (RPE) to monitor training load, but there has been little research on the practical application of sRPE in Taiwan. It has been pointed out that resting heart rate variability (HRV) is an effective way to monitor whether an athlete is in a stage of chronic fatigue. However, whether the assessment of HRV during exercise can reflect exhaustion or fatigue immediately have to be further assessed. In recent years, with the advancement of technology and algorithms, a technology to detect heart rate (HR) with facial images, called rPPG, has been developed. If RPE can be used with HR, HRV, vertical jump, and blood lactate monitoring to determine the relationship between the training impulse indexes and acute fatigue and verifies the feasibility of applying rPPG technology to training at the same time, this could potentially provide coaches with simpler and more effective monitoring indicators and methods in the future.
Purpose: This study is aimed toward exploring the trend correlation between the heart rate measured by rPPG and Polar H10 in exercise test; then exploring whether there is an opportunity to detect early signs of exhaustion by monitoring the training load indicators in the incremental exercise test in terms of making it possible for coaches to adjust training load more effectively.
Methods: 22 college students age 23.15±1.67 years who have had regular training schedules participated in the incremental exercise test on a treadmill. The heart rate and RR intervals of HRV of each participant were measured during the entire test. During the running test, the Foster’s 0-10 RPE scale was used to record the subjects’ RPE score each minute, and exercising HR, RR intervals, and energy metabolism indicators were also included. The vertical jump and blood lactate were measured before and after the running test. A one-way ANOVA was used to compare the differences among the corresponding fatigue indexes related to the various RPE scores; the stepwise regression analysis was used to explore factors that reflected blood lactate; the paired samples t-test was used to compare the difference between the HR measured using Polar H10 and the rPPG.
Results: The analytical results showed that %HRmax, energy metabolism indicators (%VO2peak and respiratory exchange rate), and each HRV index at RPE scores of 8 and 9 were significantly different than when the scores were 6 and 7 (p <.05). The three indicators of heart rate, the concentration of blood lactate, and the height of vertical jump have significant differences between the measurement time points, indicating that this incremental exercise test can effectively make the subject in an acute fatigue state. Heart rate can be used as an effective method to predict the blood lactate. The HR measured using Polar H10 and the rPPG were significantly different (p <.001).
Conclusion: The main results of this study indicated that an RPE score of 8 can be used as an early warning score indicating exhaustion. Heart rate is an effective predictor of the blood lactate. The rPPG algorithm needs to be further modified to achieve a higher proportion of consistency with Polar H10 when applied in exercise mode.
論文目次 摘要 II
表目錄 XVI
圖目錄 XVII
第壹章、 緒論 1
第一節、 研究背景與動機 1
第二節、 研究目的 5
第三節、 研究假設 5
第四節、 名詞操作型定義 6
第五節、 研究重要性 9
第貳章、 文獻探討 10
第一節、 監控訓練負荷的意義與方法 10
第二節、 急性疲勞時相關指標的變化 12
第三節、 監控訓練強度的各項指標 13
第四節、 心率變異性之應用 14
第五節、 RPE訓練衝量法的應用 17
第六節、 結語 19
第參章、 研究方法 20
第一節、 研究對象 20
第二節、 研究設計流程 20
第三節、 實驗架構 23
第四節、 最大努力運動測試 24
第五節、 研究工具 25
第六節、 資料處理與分析 29
第肆章、 研究結果 30
第一節、 基本資料 30
第二節、 最大努力運動測試中RPE分數與疲勞指標 30
第三節、 最大努力運動測試中的訓練衝量與攝氧量之關係 39
第四節、 測驗前後血乳酸、心率與神經肌肉表現之變化與關係 41
第五節、 rPPG人臉偵測與Polar H10之心率 45
第伍章、 討論 46
第一節、 最大努力運動測試中RPE分數與各疲勞指標 46
第二節、 最大努力運動測試中的訓練衝量與攝氧量之關係 49
第三節、 血乳酸、神經肌肉表現與心率之關係 50
第四節、 rPPG人臉偵測與Polar H10之心率 51
第五節、 研究範圍與限制 51
第陸章、 結論與建議 52
第一節、 研究結論 52
第二節、 未來建議 53
參考文獻 55
附錄一、受試者同意書 64
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